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Data Analyst Resume

TECHNICAL SKILLS

  • SAS, SAS Enterprise, R, SQL
  • PowerPoint, Excel (pivot table, VLOOKUP, and macro)

PROFESSIONAL EXPERIENCE

Confidential

Data Analyst

Responsibilities:

  • Gather, analyze and present economic, real estate market data, and property market trends from multiple sources in support of decision - making
  • Perform real estate marketing analysis, statistical modeling, and in-depth industry research

Confidential

SAS Programmer

Responsibilities:

  • Using SQL to retrieve data from database; Using SAS to clean and transform data; conducting statistical analysis including Wilcoxon Signed Rank-Sum Test, Paired T-Test, etc.
  • Developing SAS statistical programs, drafted technical reports, participated in communicating results of analysis.
  • Assisting GAO (Government Accountability Office) with their data request (data aggregation).

Confidential

Metrics/ Data Analyst

Responsibilities:

  • Supporting efforts to collect, compile, validate, interpret, and analyze information, formulas, and metrics, using custom developed code in R and SQL
  • Maintaining and verifying the accuracy of data; taking corrective steps to improve data quality

Confidential

Data Analyst Intern

Responsibilities:

  • Partner with business users and corporate IT to use R and SQL to acquire, manage, and analyze data and report results, including daily operations related tasks, data capture tasks, and presentation tasks
  • Ensure data quality, identify, and resolve issues with data of a logical or mathematical nature, identify trends in large datasets, use Tableau to produce interactive data visualization products to share information with analysts and report generators

Confidential

Project Assistant Intern

Responsibilities:

  • Conducting research on the DC Labor Market, including how LMI can influence alignment decisions and how students can easily access LMI while making decisions on their coursework
  • Conducting data entry and data analysis with SQL, SAS and Excel, sorting and verifying data for accuracy, creating pivot tables, organizing supplemental support.
  • Conducting data visualization and providing helpful advice for future program.

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